The most abundant prokaryotic phyla were Proteobacteria At the genus level, Nitrosopumilus 9.
Comparative analysis of the prokaryotic communities among the sampling sites. To evaluate the community diversity of each site and the differences in microbial composition among them, we calculated both the alpha and beta diversity using different indices. At the genus level, the distribution of Desulfatitalea , Desulfococcus , Desulfobacterium , and Desulfovibrio are positively correlated with the representative parameters to different extents, while four genera of Plactomycetes Planctomyces , Blastopirellula , Pirellula , and Rhodopirellula were negatively correlated.
At the family level, total volatile solids was the best indicator of the community distribution, and interestingly, was negatively correlated with three nitrifying bacteria Nitrosomonadaceae , Nitrosopumilaceae , and Nitrospinaceae. Community dissimilarities among sampling sites with pollutant vectors.
Vector matrices of the significant pollution parameters are shown by individual black lines with an arrow. The significant microbes are shown in gray. In addition to the abundance of microbes in the sediment, we also investigated the replication activity of different species, which could reflect changes in active communities. Therefore, we selected the 30 most. Among these species, the replication rates of 14 species were estimated based on sufficient genome coverage among all the samples.
By comparing the replication rate among different sampling sites, we observed that Candidatus Nitrosopumilus sp. We annotated our metagenomics sequencing data using the KEGG database and constructed the pathway profiles for the microbial communities of each sampling site. We implemented FishTaco [ 22 ], a novel algorithm for integrating taxonomic and functional comparative analyses to accurately quantify family-level contributions to functional shifts.
We performed the analyses by using the microbial communities of Centre Island and Tung Ping Chau, which were the most dissimilar in terms of pollution concentration and were found to have the most diverse prokaryotic composition according to the above analyses. KEGG Orthology annotation and taxonomic drivers of functional shifts between sites.
Taxonomic contributors to functional pathways differences between Centre Island case group and Tung Ping Chau control group based on the top 25 abundant families. The white and red diamonds refer to the taxa-based and functional-based shift scores, respectively.
The results showed an average Pearson correlation coefficient of 0. Desulfobulbaceae was found to be the main driver of the enrichment of the sulfur metabolism and benzoate degradation pathways in Centre Island. Moreover, Spirochaetaceae served as the driver of the sulfur relay system also known as sulfur transfer system in Centre Island. In addition, the trinitrotoluene degradation pathway was found to be enriched in Centre Island and was driven by Chromatiaceae and Nitrosopumilaceae.
By aligning the taxonomic profiles to a list of potential human pathogens compiled from three different sources [ 23 , 24 , 25 ], we discovered opportunistic pathogenic species from genera that comprised 4. Typical opportunistic pathogenic species of Vibrio including V.
The potential opportunistic pathogenic species P. We further calculated the alpha diversity of the putative pathogenic communities among sampling sites using both the Shannon and Simpson indices Fig. Among them, Bacillus 0. In addition, two putative pathogenic species of Treponema T.
Comparisons of abundances of potential pathogens and antibiotic resistant genes ARGs among samples. Subsequently, we investigated the resistome profiles in the different sampling sites. Among ARG mechanisms, antibiotic efflux pumps Among the ARG families, five genes that have activities against specific antibiotics were detected including aminoglycoside, beta-lactamase, fluoroquinolone, tetracycline, and the chloramphenicol resistance gene Fig.
Microbial communities inhabiting marine sediments are extremely diverse due to the complex physicochemical gradients therein [ 26 ]. Community dynamics are affected by human activities, particularly those related to water chemistry and quality [ 13 ]. Hong Kong has a diverse distribution of highly urbanized and relatively undisturbed coastal environments [ 27 ] and provides a perfect opportunity to assess the relationship between microbial communities and different levels of perturbation.
Earlier studies have investigated the community of bacteria and ARGs in marine sediments of Hong Kong using both clone libraries and metagenomics [ 7 , 28 , 29 ]. However, they were unable to identify clear patterns in either bacterial communities or ARGs. To fill this gap, we constructed a comprehensive pipeline for the proof-of-concept analysis of the microbiome communities, their functional diversity, and the resistome as affected by human activities and pollution levels.
Throughout our analysis, we provided evidence of the impact of different pollution levels on the diversity of microbial communities and their functional-associated genes as well as the risks of increased levels of ARGs and pathogens. Regarding the prokaryotic profile, we observed an enrichment of a number of phyla tightly associated with the human gut and terrestrial biomes in the most polluted areas.
In our study, Planctomycetes was the fourth most abundant phylum among the samples, and its abundance was significantly decreased at Centre Island compared to Tung Ping Chau. Combined with the pollution data from the sampling sites, our study suggests that Planctomycetes may also serve as an important potential water quality indicator.
By evaluating the microbial diversity at the community level, we observed clear differentiation among the sampling sites—especially between Centre Island and Tung Ping Chau—and coherence with the distribution of representative pollutants. Interestingly, at the genus level, the four sulfate-reducing microbes SRM Desulfatitalea , Desulfococcus , Desulfobacterium , and Desulfovibrio were found to be positively correlated with pollution levels, suggesting that eutrophication increases the abundance of SRM.
Previous studies in marine sediments of Hong Kong had also reported the relationship between SRM and pollution levels. For instance, pollutants may influence the relative abundance of SRMs to total microbes under a unimodal paradigm while low concentrations of pollutants will decrease relative abundance of SRMs in total microbes [ 7 ]. Moreover, with the clone library methods, unique SRM members related to the polluted harbor environment and estimated SRM richness correlated with several environment factors [ 29 ].
In our study, we also implemented a novel algorithm, based on sequencing coverage, which was used to calculate an index of replication iRep for estimating changes in the active microbial communities [ 21 ]. Ruegeria conchae had the highest replication rate among all sites, which is consistent with previous studies [ 37 , 38 ]. Interestingly, the active community analysis revealed additional changes in bacterial spp. Two species of Thaumarchaeota—Candidatus Nitrosopumilus sp. NF5 and Candidatus Nitrosoarchaeum koreensis —which are responsible for the major ammonia-oxidizing process [ 39 , 40 ] in sediment, replicated faster in sites with high water quality i.
The concordance of replication rate with relative abundance not only confirms the adaptation of Thaumarchaeota to low-ammonia conditions but also reveals the mechanism by which it can maintain a high abundance. When investigating pathogenicity among all sites, we observed that Vibrio , including its three opportunistic pathogenic species, V. These disease-causing strains of Vibrio are associated with infectious diarrhea and are commonly carried by marine animals including crustaceans [ 41 ].
Pseudomonas aeruginosa , the second most abundant potential pathogenic species in our analysis, is a multidrug resistant pathogen and causes a wide variety of serious infectious diseases including meningitis, pneumonia, and septicemia [ 42 , 43 , 44 ]. The alpha diversity calculated from only putative pathogenic microbes decreased significantly from Centre Island to Tung Ping Chau, indicating that pollution inputs influence the local potential pathogen composition.
Furthermore, nine opportunistic pathogenic genera were enriched at the most polluted site. Considering that coastal waters are the most impacted by human activities including recreation e. Based on the evidence above, we observed a connection between the extent of pollution and the abundance and diversity of pathogenic organisms in marine sediments. Pinpointing the drivers of these patterns is complex as feedback loops between both biotic and abiotic process function across multiple spatial and temporal scales.
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For example, healthy and biodiverse marine ecosystems buffer against the proliferation of bacterial pathogens [ 5 , 45 ] but foundational species can be sensitive to pollutants. The persistence of diverse coral assemblages at Tung Ping Chau may contribute to increased pathogen resistance while the eutrophication of Tolo Harbour and disappearance of coral communities [ 27 ] may have reduced this important ecosystem service. More direct links between human activity and pollution stress can be inferred from our antibiotic resistance analysis which shows an increase in the dominant resistance mechanisms and abundance of ARGs.
It is well known that efflux pumps are the predominant resistance mechanism in sediments [ 17 ], and our results further provide the direct evidence that an increase in efflux pump-related genes is correlated to an increase in pollution [ 46 ]. In other words, the increasing efflux pump mechanisms in the microbes would greatly contribute to antibiotic resistance and further presented a growing threat to antibiotic therapy and a major challenge for antibiotic development. Our investigation of the microbiome composition and functionality in marine sediments revealed that microbe communities are likely influenced by human activity and pollution discharge.
Through our analysis, we also identified several microbes within the Planctomycetes phylum that may serve as useful bio-indicators of water quality. The relationships among sediment microbial communities and water quality presented here set the stage for a valuable reference database for environmental assessments and public policy. Therefore, we strive for the continuous sampling of these as well as additional sites in Hong Kong to provide new insight into the interactions between humans and coastal marine ecosystems.
These data were obtained from the sediment samples collected in August at the benthic sediment sampling locations. DNA concentrations 2.
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The raw sequencing paired-end reads passed standard quality control after the adapter regions and low-quality reads were removed, as per Li et al. The relative abundances of each taxa were further distilled from the LCA results for each taxonomic level. Prokaryotic community profiles were constructed at phylum, family, and genus levels for further statistical analysis. Additionally, potential pathogenic species and genera were taxonomically identified using three publicly available lists of putative pathogens [ 23 , 24 , 25 ] and further summarized to genus level for statistical comparisons.
The organisms appearing on the list were regarded as opportunistic pathogens and the species containing at least one opportunistic pathogenic strain were marked as putative pathogenic species. Alpha diversity indices detailing microbial community composition within each sample was calculated using vegan [ 51 ] in R. Both the Shannon and Simpson indices were used for alpha diversity evaluation based on the relative abundance of each taxonomic level.
For estimating community dissimilarities, both Bray-Curtis and Euclidean distances were calculated by phyloseq [ 52 ] and vegan [ 51 ] based on the relative abundance of each taxon at different levels. To estimate the replication rate of the 30 most abundant species, an in-house genome database was constructed manually by obtaining the draft or complete genomes of the target species either contig or scaffold from the NCBI Genome database. The high-quality metagenomic reads were mapped to the in-house genome database by Bowtie2 [ 53 ].
The mapped results of each target species were further manipulated with SAMtools [ 54 ] and were used for measuring replication rates with iRep [ 21 ]. The identified KO genes were further annotated into different pathways based on predefined collections in the KEGG database and were quantified by read counts. The prokaryotic taxonomic profiles of the 25 most abundant families among samples and the pathway profile were integrated to quantify taxa-specific contributions to functional shifts using FishTaco [ 22 ].
Three replicate samples were analyzed. The pollution parameters were served as fitted vectors in the above multidimensional scaling for testing the correlation between community distributions and pollution levels. Spearman correlations were further performed between taxonomic abundance and KO pathways among the four sampling sites based on the FishTaco results using the correlation function in R. Packages including ggplot2 and gplots in R and matplotlib in Python were used for visualization purposes.
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Marine pollution diagnosis and therapy
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